Generalization Bounds for Neural Network Based Decoders
Explore generalization bounds for neural network decoders, examining their implications for information-theoretic approaches in trustworthy machine learning.
Majorizing Measures, Codes, and Information
Explore the connections between majorizing measures, coding theory, and information theory in machine learning, with insights from Maxim Raginsky.
Train a PyTorch Neural Network Step-by-Step - PyTorch Deep Learning
Learn to build and train a PyTorch neural network for image classification, achieving 85% accuracy on Fashion MNIST. Covers data preparation, network architecture, loss functions, optimization, and model visualization.
GPT-3 Tutorial: Building Projects for Email Writing and Ad Slogan Generation
Hands-on tutorial exploring GPT-3's capabilities through practical projects, including LaTeX translation, email composition, and ad slogan generation. Covers API setup, model parameters, and unexpected results.
Ethics - Full Stack Deep Learning - Spring 2021
Explore AI ethics, covering long-term challenges, hiring practices, fairness, representation, and best practices. Gain insights into crucial ethical considerations for AI development and implementation.
Spotlight on Australia and New Zealand - NAB's Tech Support Chatbot
Discover how NAB improved employee productivity and customer experience with an AI-powered tech support chatbot using Microsoft Azure Cognitive Services and Bot Framework.
Build ChatGPT Chatbots with LangChain Memory - Understanding and Implementing Memory in Conversations
Explore different memory types for ChatGPT chatbots using LangChain, including buffer, summary, window, and vectorstore memory. Learn implementation techniques for coherent conversations.
LangChain Models- ChatGPT, Flan Alpaca, OpenAI Embeddings, Prompt Templates & Streaming
Explore LangChain's capabilities with chat models, embeddings, and prompt templates. Learn to enhance responses and stream output for efficient language model integration.
Learn Computer Vision Web Development in 2 Hours
Comprehensive introduction to computer vision web development, covering HTML/CSS layout, OpenCV integration, and image processing techniques for creating interactive photo editing applications.
ControlNet Tutorial
Comprehensive tutorial on ControlNet 1.1 for Stable Diffusion, covering installation, usage, input creation with PoseMyArt, and new features. Ideal for AI art enthusiasts looking to enhance their image generation skills.
Generate Studio Quality Realistic Photos With Kohya LoRA Stable Diffusion Training - Full Tutorial
Comprehensive guide to generating studio-quality AI photos using Kohya LoRA Stable Diffusion training, covering installation, parameter settings, dataset preparation, and advanced techniques for optimal results.
ControlNET - What You Need to Know
Comprehensive guide on ControlNET 1.1, covering installation, new models, OpenPose features, and Tile-Resampling for enhanced image quality and detail in AI-generated visuals.
LangChain Agents - Build Personal Assistants for Your Data
Learn to build AI personal assistants using LangChain agents, interact with APIs and tabular data, and explore advanced LLM applications in this Q&A session with industry experts.
Search and Discovery in News and Research - Dr. Anju Kambadur
Explore Bloomberg's AI-driven search and discovery system for financial news, leveraging machine learning and NLP to parse unstructured data and provide valuable insights for clients.
The LangChain Cookbook Part 2 - Beginner Guide to 9 Use Cases
Explore 9 practical LangChain use cases, from summarization to agents, with hands-on examples and expert guidance for leveraging AI in various applications.
Stable Diffusion- Applying ControlNet to Character Design - Part 2
Explore advanced techniques in AI-powered character design using ControlNet 1.1, including inpainting, targeted variations, and contextual upscaling for enhanced digital illustrations and PNGtubers.
ChatGPT - Water Sector Applications
Explore AI and large language models in water industry applications, including ChatGPT capabilities, live demos, software integration, and potential risks and opportunities.
Approximating Many-Electron Wave Functions Using Neural Networks - IPAM at UCLA
Explore neural network applications in quantum mechanics, focusing on Fermionic neural networks for approximating many-electron wave functions and enhancing variational quantum Monte Carlo methods.
Message Passing Neural Networks for Atomistic Systems - Molecules
Explore message passing neural networks for molecular systems, focusing on their application in quantum mechanics and multiscale approaches to atomistic modeling.
Learning to Explore with Scalable Supervision - IPAM at UCLA
Discover efficient reinforcement learning techniques for robotic control, balancing self-supervision and human guidance to overcome exploration challenges in high-dimensional spaces.
Some Mathematical Theorems on Agreement and Learning in Networks - IPAM at UCLA
Explore mathematical theorems on agreement and learning in networks, presented by MIT's Elchanan Mossel at IPAM's Mathematics of Collective Intelligence Workshop.